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Record W1979720319 · doi:10.5014/ajot.60.4.442

The Use of Automated Prompting to Facilitate Handwashing in Persons With Dementia

2006· article· en· W1979720319 on OpenAlexaff
Katrinka-Lee Labelle, Alex Mihailidis

Bibliographic record

VenueAmerican Journal of Occupational Therapy · 2006
Typearticle
Languageen
FieldHealth Professions
TopicOccupational Therapy Practice and Research
Canadian institutionsUniversity of TorontoWomen's College HospitalSunnybrook Health Science Centre
Fundersnot available
KeywordsDementiaIntervention (counseling)PopulationPsychologyOccupational therapyClinical psychologyMedicinePsychiatry

Abstract

fetched live from OpenAlex

As the number of people living with dementia increases, occupational therapists are challenged with finding innovative, evidence-based ways to enable daily occupations. The use of computer technology is explored in this study as one potential intervention for this population. An automated prompting system was modified to provide both verbal and audiovisual prompts, and 8 participants with Standardized Mini-Mental State Examination (SMMSE) scores as low as 3/30 were followed over 60 trials to determine which prompting method was more effective in reducing caregiver interactions. Overall, the participants were able to complete more steps with the assistance of either automated prompt and required fewer caregiver interactions. Audiovisual prompting significantly reduced the number of caregiver interactions required. These results lend further support to the use of an automated prompting system but suggest that there are individual factors influencing the efficacy of the prompting mode, for which occupational therapists are well suited to assess and monitor.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.033
Threshold uncertainty score0.346

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.284
GPT teacher head0.471
Teacher spread0.188 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations53
Published2006
Admission routes1
Has abstractyes

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